A review on modeling of solar photovoltaic systems using artificial neural networks,fuzzy logic,genetic algorithm and hybrid models

The uncertainty associated with modeling and performance prediction of solar photovoltaic systems could be easily and efficiently solved by artificial intelligence techniques. During the past decade of 2009 to 2019, artificial neural network (ANN), fuzzy logic (FL), genetic algorithm (GA) and their hybrid models are found potential artificial intelligence tools for performance prediction and modeling of solar photovoltaic systems. In addition, during this decade there is no extensive review on applicability of ANN, FL, GA and their hybrid models for performance prediction and modeling of solar photovoltaic systems. Therefore, this article focuses on extensive review on design, modeling, maximum power point tracking, fault detection and output power/efficiency prediction of solar photovoltaic systems using artificial intelligence techniques of the ANN, FL, GA and their hybrid models. In addition, the selected articles on the solar radiation prediction using ANN, FL, GA and their hybrid models are also summarized. Total of 122 articles are reviewed and summarized in the present review for the period of 2009 to 2019 with 90 articles in the field of {ANN, FL, GA and their hybrid models} + solar photovoltaic systems and 32 articles in the field of {ANN, FL, GA and their hybrid models} + solar radiation. The review shows the suitability and reliability of ANN, FL, GA and hybrid models for accurate prediction of the solar radiation and the performance characteristics of solar photovoltaic systems. In addition, this review presents the guidance for the researchers and engineers in the field of solar photovoltaic systems to select the suitable prediction tool for enhancement of the performance characteristics of the solar photovoltaic systems and the utilization of the available solar radiation.     

Does thermal control improve visual satisfaction? Interactions between occupants’ self-perceived control,visual, thermal,and overall satisfaction

Occupants’ satisfaction had been researched independently related to thermal and visual stimuli for many decades showing among others the influence of self-perceived control. Few studies revealed interactions between thermal and visual stimuli affecting occupant satisfaction. In addition, studies including interactions between thermal and visual stimuli are lacking different control scenarios. This study focused on the effects of thermal and visual factors, their interaction, seasonal influences, and the degree of self-perceived control on overall, thermal, and visual satisfaction. A repeated-measures laboratory study with 61 participants running over two years and a total of 986 participant sessions was conducted. Mixed model analyses with overall satisfaction as outcome variable revealed that thermal satisfaction and visual satisfaction are the most important predictors for overall satisfaction with the indoor environment. Self-perceived thermal control served as moderator between thermal satisfaction and overall satisfaction. Season had slight influence on overall satisfaction. Random effects explained the highest amount of variance, indicating that intra- and interindividual differences in the ratings of satisfaction are more prevalent than study condition. Future building design and operation plans aiming at a high level of occupant satisfaction should consider personal control opportunities and take into account the moderating effect of control opportunities in multimodal interactions.     

Experimental investigations and constitutive modeling of cyclic interface shearing between HDPE geomembrane and sandy gravel

This paper presents the results of experimental investigations and constitutive modeling of cyclic interface shearing between HDPE geomembrane and cohesionless sandy gravel. A series of cyclic interface shear tests was performed using a large-scale cyclic shear apparatus with servo controlled system. Particular attention was paid to the influences of the amount of shear-displacement amplitude, number of cycles, shear rate and the normal pressure on the mechanical response. The experimental results show that the path of the shear stress against the cyclic shear displacement is strongly non-linear and forms a closed hysteresis loop, which is pressure dependent, but almost independent of the shear rate. For small shear-displacement amplitudes, the obtained damping ratio is significantly greater than zero, which is different to the behavior usually observed for cyclic soil to soil shearing. In order to describe the pressure dependency of the hysteresis loop using a single set of constitutive parameters, new approximation functions are put forward and embedded into the concept of the Masing rule. Further, a new empirical function is proposed for the damping ratios to capture the experimental data for both small and large cyclic shear-displacement amplitudes. The included model parameters are easy to calibrate and the new functions may also be useful in developing enhanced constitutive models for the simulation of the cyclic interface shear behavior between other geosynthetics and soils.     

Towards patient‐centered packaging design: An industry perspective on processes,functions, and constraints

Medication packaging is essential to provide patients with guidance and correct use of their medicines for effective treatment. This research aims to increase knowledge about the medication packaging innovation process and its uptake towards patient‐centered packaging design. The study applied a qualitative research approach based on data from 25 in‐depth interviews with stakeholders involved in medication packaging design. The empirical data analysis revealed four themes that can improve and advance user‐centered packaging design: medication packaging innovation process, medication packaging functions and features, medication packaging design constraints, and patient‐centered medication packaging design. The findings suggest that medication packaging design is strongly affected by an emphasis on protective and safety packaging functions rather than on patients' needs. Packaging innovation usually is constrained by rigid incremental development processes, where compliance with regulations, extensive documentation, avoidance of manufacturing complexity, and considerations on cost prevail. These findings are discussed in relation to the three most evident trade‐offs for patient‐centered design: protection versus openability, utility versus cost, and complexity of manufacturability versus complexity of use. This research contributes with valuable input and additional evidence about the necessary shift to a user‐centered approach in a field that has not been design driven. This input complements previous research and provides an opportunity for industry decision makers and policy makers to lead patient‐centered packaging design that can benefit patients and relieve overloaded health care systems.     

Room temperature response and enhanced hydrogen sensing in size selected Pd-C core-shell nanoparticles: Role of carbon shell and Pd-C interface

In the present work, the effect of carbon shell around size selected palladium (Pd) nanoparticles on hydrogen (H₂) sensing has been studied by investigating the sensing response of Pd-C core-shell nanoparticles having a fixed core size and different shell thickness. The H₂ sensing response of sensors based on Pd and Pd-C nanoparticles deposited on SiO₂ and graphene substrate has been measured over a temperature range of 25 °C–150 °C. It is observed that Pd-C nanoparticle sensor shows higher sensitivity with increase in shell thickness and faster response/recovery in comparison to that of Pd nanoparticle samples. Pd-C nanoparticles show room temperature H₂ sensitivity in contrast to Pd nanoparticles which respond only at higher temperatures. Role of carbon shell is also understood by investigating H₂ sensing properties of Pd and Pd-C nanoparticles on graphene substrates. These results show that higher catalytic activity and electronic interaction at Pd-C interface, a complete coverage and protection of Pd surface by carbon and presence of structural defects in nanoparticle core are important for room temperature and higher sensing response.     

Reality-based interaction affecting mental workload in virtual reality mental arithmetic training

ABSTRACT

The concept of digital game-based learning (DGBL) evolves rapidly together with technological enhancements of virtual reality (VR) and smart phones. However, the mental workload (MWL) that VR-training applications demand and motivational qualities originating from user experience (UX) should be identified in order to create effective and enjoyable training/learning challenges that fit with individual users’ capabilities. This study examined the effects of reality-based interaction (RBI) and VR on measures of student motivation and MWL, in a mental arithmetic game for secondary school pupils. In a randomised controlled trial with sixty school children, a mental arithmetic game was tested with three different interaction and two different presentation methods – VR RBI, VR head-mounted-display tapping and tablet flick-gesture. Results found a significant effect of RBI on MWL but no differences in enjoyment of training were found between VR-experience and tablet training-experience. In fact, adding the gaming-context to the mental arithmetic task created an enjoyable, motivating experience regardless of presentation or interaction-style.     

Three-dimensional immersed finite-element method for anisotropic magnetostatic/electrostatic interface problems with nonhomogeneous flux jump

Anisotropic diffusion is important to many different types of common materials and media. Based on structured Cartesian meshes, we develop a three-dimensional (3D) nonhomogeneous immersed finite-element (IFE) method for the interface problem of anisotropic diffusion, which is characterized by an anisotropic elliptic equation with discontinuous tensor coefficient and nonhomogeneous flux jump. We first construct the 3D linear IFE space for the anisotropic nonhomogeneous jump conditions. Then we present the IFE Galerkin method for the anisotropic elliptic equation. Since this method can efficiently solve interface problems on structured Cartesian meshes, it provides a promising tool to solve the physical models with complex geometries of different materials, hence can serve as an efficient field solver in a simulation on Cartesian meshes for related problems, such as the particle-in-cell simulation. Numerical examples are provided to demonstrate the features of the proposed method.     

A comprehensive appraisal of perceptual visual complexity analysis methods in GUI design

Graphical or Visual User Interface (GUI) is recognized as one of the most important application components for safety critical and business oriented software systems. It is highly advantageous for GUI designers and application developers to analyze the visual complexity of a GUI and predict users’ perception and judgment during the design phase. Although in recent years, various methods have been developed for visual complexity analysis, these have not been widely used due to applicability, practicality and validity issues. In this respect, we have conducted a comprehensive review of studies and methods in visual complexity analysis. After identifying and analyzing 85 research studies, we grouped the visual complexity analysis methods and accordingly a taxonomy is presented. Furthermore, conceptual comparison of the methods is given and gap analysis as well as possible future directions are provided. According to the our findings, major gaps for each visual complexity analysis method may be stated as follows: 1) In metric-model based methods, there is a lack of information about the suitability of the metric-model created for analysis, since the extent to which each metric contributes to visual complexity analysis is still not known exactly. 2) In heuristic- based methods, the extracted rule set is not yet extendable enough beyond the use for specific GUIs. 3) While the visual complexity analysis could be considered as a kind of computer vision task, there exist limited studies that does so. Therefore, generalizable solutions based on machine learning techniques seem to be a promising research direction to develop efficient approaches.